What specific tuning strategies actually work for reducing false positives in endpoint detection tools without missing sophisticated living off the land attacks?
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The searches the AI actually ran for this prompt.
SEED QUERY
What specific tuning strategies actually work for reducing false positives in endpoint detection tools without missing sophisticated living off the land attacks?
1 real search · 1 real-search pass
EDR alert tuning false positives behavioral detection exclusions Microsoft Defender guidance LOTL MITRE ATT&CK detection engineeringGoogle ↗
OBSERVED
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Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
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Searches and sources
ChatGPT1 real searches · gpt-6
EDR alert tuning false positives behavioral detection exclusions Microsoft Defender guidance LOTL MITRE ATT&CK detection engineering Google ↗
- Address false positives/negatives in Microsoft Defender for Endpoint - Microsoft Defender for Endpoint · learn.microsoft.com
- Overview of exclusions and indicators in Microsoft Defender for Endpoint - Microsoft Defender for Endpoint · learn.microsoft.com
- MITRE ATT&CK · attack.mitre.org